Bootstrap Confidence Intervals

Repeated sampling from a population may be impractical, expensive or not possible (sample items destroyed during sampling)

If we cannot resample from the population, (the true sampling distribution is unavailable) then we resample from the best approximation of the population we have - which is the sample itself (producing a bootstrap distribution)

Use the original sample to represent the population.
Take repeated re-samples from the ordinal sample.
Use these re-samples to calculate an estimate for the population statistic (mean or median)
This is called Bootstrapping

The re-sampling produces a distribution of means (or medians) which form a distribution

The bootstrap confidence interval provides an estimate for the population mean

Review maui/hectors dolphin data sets

Assuming our sample was representative of the population then the bootstrapped confidence interval can be used as an estimate of the true population mean (or median)